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Platform for building RL environments and post-training datasets.

Assemble Bench: Benchmarking Robot Models on Contact-Rich Assembly

How HUD Delivers Frontier Model Training Gyms on Railway

Run an RL Coding Environment at Scale with HUD and Daytona

RL Environments and RL for Science: Data Foundries and Multi-Agent Architectures

Research Engineer, Privacy and Anonymization

HUD is building infrastructure for reinforcement learning training data and evaluations for frontier AI agents. The Research Engineer will build privacy and anonymization systems to detect and transform sensitive information, develop production data-protection pipelines, and evaluate privacy risk while preserving data utility for AI training.

Senior Software Engineer, Infrastructure

HUD is building infrastructure for creating reinforcement learning training data and evaluations for frontier AI agents, along with a marketplace for selling these resources to frontier labs. The Senior Software Engineer, Infrastructure will own the reliability, scalability, performance, cost, and developer experience of HUD’s core infrastructure and backend systems across AWS, Kubernetes, Terraform, CI/CD, observability, and backend services.

Lead Research Engineer, Data Quality

HUD is building infrastructure for reinforcement learning training data and evaluations for frontier AI agents. The Lead Research Engineer, Data Quality will lead the data quality team, develop systems to evaluate and improve training data, and establish scalable quality standards, validation methods, and feedback workflows.

Research Engineer

HUD is building infrastructure to create RL training data and evals for frontier AI agents, and they are seeking research engineers to help build out QA for training data created by companies using HUD’s infrastructure. The role involves defining quality standards, building tooling for dataset audits, and partnering with data vendors to improve data generation processes.

Research Engineer, Synthetic Data

HUD is building infrastructure for RL training data and evaluations for frontier AI agents. The Research Engineer will build a synthetic data pipeline by creating, generating, validating, and analyzing synthetic training tasks that improve AI agent capabilities.

HUD is building infrastructure for RL training data and evaluations for frontier AI agents. They are seeking research engineers to develop quality assurance systems for training data generated by companies using their infrastructure.

Research Engineer (General)

HUD is building infrastructure for training data and evaluations for frontier AI agents. The Research Engineer will build systems for creating and evaluating agent training environments, improve data quality, develop research and data tools, and create metrics for assessing tasks, environments, and evaluations.

Research Engineer, Benchmarks

HUD is building infrastructure for reinforcement learning training data and evaluations for frontier AI agents, along with a marketplace for frontier labs. The Research Engineer will design, implement, and validate technically rigorous benchmarks for domain-specific agent tasks, build supporting infrastructure, analyze performance, and document results.

Full-Stack Software Engineer, Reinforcement Learning

HUD is building infrastructure for reinforcement learning training data, evaluations, and a marketplace for frontier AI labs. The company is seeking a Full-Stack Software Engineer, Reinforcement Learning to build product surfaces, backend systems, APIs, dashboards, internal tools, vendor workflows, and observability systems that power its RL data engine.

Growth Lead

HUD is building infrastructure to create RL training data and evals for frontier AI agents, as well as a marketplace to sell these to frontier labs. They are seeking a Growth Lead to connect with candidates, AI engineers, and key figures in the AI ecosystem, while also defining culture and values and managing recruiting processes.